Hi, I'm Musa β an aspiring data scientist turning complex data into clear insights.
I am passionate about working at the intersection of data, innovation, and strategy, constantly seeking to transform raw numbers into actionable insights. This portfolio is a showcase of my skills and projects in data analysis, problem-solving, and delivering innovative solutions. Explore how I use data to drive impact and create value.
Languages: Python, SQL, R, MATLAB
Tools & Libraries: Tableau, Power BI, Advanced Excel, Google Analytics, Pandas, Scikit-learn, Matplotlib, Numpy, StatsModels, Plotly
Statistical Methods: Regression Models, A/B Testing, Hypothesis Testing, Time Series Analysis
B.S., Computer Science β Oregon State University (Expected May 2026)
B.A., Public Health Policy β University of California, Irvine (Graduated June 2022)
I currently serve as a Business Analyst at 1800 Hiring Inc., where I collaborate with diverse teams to design data-driven solutions that optimize recruitment workflows and enhance client outcomes. My experience includes building analytics platforms and developing interactive dashboards that help stakeholders monitor performance and identify business trends.
Previously, I worked as a Data Analyst Intern at Information Direct, where I analyzed large datasets, built customer behavior models, and ensured compliance with privacy and regulatory standards using SQL, Tableau, and Excel.
My research experience at UCI Healthβs Beckman Laser Institute allowed me to apply Python and MATLAB to develop predictive healthcare models and contribute to clinical trials through data-driven analysis and optimization.
Synthea Healthcare Analytics
Conducted public health analysis on synthetic EHR data using ICD and CPT codes. Merged encounter, procedure, and condition datasets to surface trends across gender and age groups, with encounter-level diagnosis-to-procedure modeling in Python.
Fog of War Chess
Created a Python-based chess variant with Fog of War rules, enabling players to only see their pieces and valid moves, with dynamic board perspectives for players and observers.
NFL Big Data Bowl Competition 2025
Analyzed player tracking data to uncover insights into pre-snap and post-snap dynamics, using Python and SQL to help visualize team tendencies and player strategies.
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